Adjust GPU duration and number of epochs

app.py

@@ -48,7 +48,7 @@ index_to_class = dict((v,k) for k,v in class_to_index.items())
 names_to_ids = lambda labels: np.array([class_to_index.get(x) for x in labels])
 train_labels = names_to_ids(labels)
 
-@spaces.GPU(duration=200)
+@spaces.GPU(duration=150)
 def load_model():
    
 
@@ -70,7 +70,7 @@ def load_model():
     val_labels = names_to_ids(val_labels)
     h = model.fit(
         padded_train_seq, train_labels, validation_data=(val_seq, val_labels),
-        epochs=20,
+        epochs=8,
         callbacks=[
             tf.keras.callbacks.EarlyStopping(monitor='val_accuracy', patience=2)
         ]